Search Results for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files" - Page 43
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Showing 3563 open source projects for "/storage/emulated/0/android/data/net.sourceforge.uiq3.fx603p/files"
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Get full visibility and control over your tasks and projects with Wrike.Wrike offers world-class features that empower cross-functional, distributed, or growing teams take their projects from the initial request stage all the way to tracking work progress and reporting results.
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The AI-powered unified PSA-RMM platform for modern MSPs.SuperOps.ai is the only PSA-RMM platform powered by intelligent automation and thoughtfully crafted for the new-age MSP. The platform also helps MSPs manage their projects, clients, and IT documents from a single place.
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Reproducible-research
A Reproducible Data Analysis Workflow with R Markdown, Git, Make, etc.
In this tutorial, we describe a workflow to ensure long-term reproducibility of R-based data analyses. The workflow leverages established tools and practices from software engineering. It combines the benefits of various open-source software tools including R Markdown, Git, Make, and Docker, whose interplay ensures seamless integration of version management, dynamic report generation conforming to various journal styles, and full cross-platform and long-term computational reproducibility. ... -
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ClimateMachine.jl
Earth System Model that automatically learns from data
...The ClimateMachine solves three-dimensional partial differential equations for the distributions of water, momentum, energy, and tracers such as carbon in the atmosphere, oceans, and on land. The ClimateMachine will harness a wide range of Earth observations and data generated computationally to predict the evolution of Earth’s climate and features such as droughts, rainfall extremes, and high-impact storms. -
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OzGIS free open-source mapping system
Analysis and display of Census, business, government attribute data
OzGIS is an extensive mapping system for the analysis and display of geographically referenced data. Map data are downloaded from Census bureaux and map agencies or extracted from your own databases. The system can be used to to support management decisions associated with, for example, government planning, marketing, sales, site and personnel location, advertising and research. Systems for Windows, Mac and Ubuntu, source code, sample data files and manuals are included. ... -
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ArrayFire.jl
Julia wrapper for the ArrayFire library
ArrayFire is a library for GPU and accelerated computing. ArrayFire.jl wraps the ArrayFire library for Julia, and provides a Julia interface. Install ArrayFire library: either download a binary from the official site, or you can build from source. -
Unrivaled Embedded Payments Solutions | NMINMI Payments is an embedded payments solution that lets SaaS platforms, Software companies and ISVs integrate, brand, and manage payment acceptance directly within their software—without becoming a PayFac or building complex infrastructure. As a full-stack processor, acquirer, and technology partner, NMI handles onboarding, compliance, and risk so you can stay focused on growth. The modular, white-label platform supports omnichannel payments, from online, mobile and in-app to in-store and unattended. Choose from full-code, low-code, or no-code integration paths and launch in weeks, not months. Built-in risk tools, flexible monetization, and customizable branding help you scale faster while keeping full control of your experience. With NMI’s developer-first tools, sandbox testing, and modern APIs, you can embed payments quickly and confidently.
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geometry-api-java
The Esri Geometry API for Java enables developers to write apps
The Esri Geometry API for Java can be used to enable spatial data processing in 3rd-party data-processing solutions. Developers of custom MapReduce-based applications for Hadoop can use this API for spatial processing of data in the Hadoop system. The API is also used by the Hive UDF’s and could be used by developers building geometry functions for 3rd-party applications such as Cassandra, HBase, Storm and many other Java-based “big data” applications. -
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ElectronDisplay.jl
An Electron.jl based figure and table display.
This package provides a display for figures, plots and tables. When you load the package, it will push a new display onto the Julia display stack and from then on it will display any value that can be rendered as png, svg, vega, vega-lite or plotly in an electron-based window. This is especially handy when one works on the REPL and wants plots or tables to show up in a nice window. -
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GPlates
Interactive visualization of plate tectonics.
GPlates is a plate-tectonics program. Manipulate reconstructions of geological and paleo-geographic features through geological time. Interactively visualize vector, raster and volume data. PyGPlates is the GPlates Python library. Get fine-grained access to GPlates functionality in your Python scripts. -
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Jupytab
Display in Tableau data from Jupyter notebooks
Jupytab allows you to explore in Tableau data which is generated dynamically by a Jupyter Notebook. You can thus create Tableau data sources in a very flexible way using all the power of Python. This is achieved by having Tableau access data through a web server created by Jupytab. -
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DISTOD
Distributed discovery of bidirectional order dependencies
The DISTOD data profiling algorithm is a distributed algorithm to discover bidirectional order dependencies (in set-based form) from relational data. DISTOD is based on the single-threaded FASTOD-BID algorithm [1], but DISTOD scales elastically to many machines outperforming FASTOD-BID by up to orders of magnitude. Bidirectional order dependencies (bODs) capture order relationships between lists of attributes in a relational table. -
Curtain LogTrace File Activity MonitoringCurtain LogTrace File Activity Monitoring is an enterprise file activity monitoring solution. It tracks user actions: create, copy, move, delete, rename, print, open, close, save. Includes source/destination paths and disk type. Perfect for monitoring user file activities.
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eMatrix
A C++ Matrix Library
eMatrix is a lightweight matrix library developed in C++. EMatrix is designed to help solve engineering problems requiring linear algebra. eMatrix is OS independent and is fairly portable. New features include inv(A) and det(A). -
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Limada (Linked Marked Data) is a framework for managing relationships of data in non-hierarchical structures, where the individual elements are interconnected in complex ways. The philosophy behind: Information is connection, is relationship of data.
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JuliaDB.jl
Parallel analytical database in pure Julia
JuliaDB is a package for working with large persistent data set. JuliaDB provides distributed table and array datastructures with convenient functions to load data from CSV. JuliaDB is Julia all the way down. This means queries can be composed with Julia code that may use a vast ecosystem of packages. -
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IPyPublish
Workflow for creating and editing publication ready scientific reports
A program for creating and editing publication-ready scientific reports and presentations, from one or more Jupyter Notebooks. Dynamically (and reproducibly) explore data, run code, and output the results. Dynamically edit and visualize the basic components of the document (text, math, figures, tables, references, citations, etc). Have precise control over what elements are output to the final document and how they are layed out and typeset. Also be able to output the same source document to different layouts and formats (pdf, HTML, presentation slides, etc). -
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repo2docker GitHub Action
A GitHub action to build data science environment images
Trigger repo2docker to build a Jupyter enabled Docker image from your GitHub repository and push this image to a Docker registry of your choice. This will automatically attempt to build an environment from configuration files found in your repository. Images generated by this action are automatically tagged with both latest and <SHA> corresponding to the relevant commit SHA on GitHub. Both tags are pushed to the Docker registry specified by the user. If an existing image with the latest tag already exists in your registry, this Action attempts to pull that image as a cache to reduce uncessary build steps. -
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CNN Explainer
Learning Convolutional Neural Networks with Interactive Visualization
In machine learning, a classifier assigns a class label to a data point. For example, an image classifier produces a class label (e.g, bird, plane) for what objects exist within an image. A convolutional neural network, or CNN for short, is a type of classifier, which excels at solving this problem! A CNN is a neural network: an algorithm used to recognize patterns in data. Neural Networks in general are composed of a collection of neurons that are organized in layers, each with their own learnable weights and biases. ... -
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Forecasting Best Practices
Time Series Forecasting Best Practices & Examples
...Rather than creating implementations from scratch, we draw from existing state-of-the-art libraries and build additional utilities around processing and featuring the data, optimizing and evaluating models, and scaling up to the cloud. The examples and best practices are provided as Python Jupyter notebooks and R markdown files and a library of utility functions. -
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Optimus
Agile Data Preparation Workflows made easy with Pandas
Easily write code to clean, transform, explore and visualize data using Python. Process using a simple API, making it easy to use for newcomers. More than 100 functions to handle strings, process dates, urls and emails. Easily plot data from any size. Out-of-box functions to explore and fix data quality. Use the same code to process your data in your laptop or in a remote cluster of GPUs. -
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ArgCheck.jl
Package for checking function arguments
Package for checking function arguments. @argcheck code is as fast as @assert or a hand written if. That being said it is possible to erase argchecks, much like one can erase bounds checking using @inbounds. This feature is currently experimental. It may be silently changed or removed without increasing the major ArgCheck version number. -
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DBSolveOptimum
The software for systems biology/pharmacology modeling
...It is a succession and extension of DBSolve 5 and DBSolve 7, which were popular tools for systems biology. In addition to the capabilities of these software packages, DBSolveOptimum is implemented with new tools for extended data analysis and multiple simulations, which are important for simulation of virtual clinical trials and application of modern modeling techniques, like quantitative systems pharmacology, to problems arising in drug research and development. By this time, DBSolveOptimum has been successfully tested and applied for the development and analysis of both systems pharmacology and conventional PK/PD models of drugs. ... -
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QuiclickRNAseq
An integrated pipeline for RNA-seq analysis
Quiclick is a python framework for RNA-seq data analysis, including data trimming, mapping, counting and RNA editing analysis. -
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NLOptControl.jl
nonlinear control optimization tool
This software solves nonlinear control problems at a high level very quickly. -
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КЛАДР-браузер
КЛАДР-браузер
Программа для просмотра данных из КЛАДР. 1) Скачиваете официальные базы КЛАДР-а тут https://www.gnivc.ru/technical_support/classifiers_reference/kladr/ 2) Распаковываете полученный архив в любую папку на компьютере (в папке должны оказаться файлы ALTNAMES.DBF, DOMA.DBF, FLAT.DBF, KLADR.DBF, SOCRBASE.DBF, STREET.DBF). 3) Запускаете мою программу и выбираете File->Create, а там указываете папку куда была распакована база данных КЛАДР и её имя (при желании). Запускаете импорт и ждете... -
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CUDAnative.jl
Julia support for native CUDA programming
The programming support for NVIDIA GPUs in Julia is provided by the CUDA.jl package. It is built on the CUDA toolkit and aims to be as full-featured and offer the same performance as CUDA C. The toolchain is mature, has been under development since 2014, and can easily be installed on any current version of Julia using the integrated package manager. -
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StellarGraph
Machine Learning on Graphs
...The StellarGraph library offers state-of-the-art algorithms for graph machine learning, making it easy to discover patterns and answer questions about graph-structured data. It can solve many machine learning tasks. Graph-structured data represent entities as nodes (or vertices) and relationships between them as edges (or links), and can include data associated with either as attributes. For example, a graph can contain people as nodes and friendships between them as links, with data like a person’s age and the date a friendship was established. ...
